Modularity in NEAT Reinforcement Learning Networks. (arXiv:2205.06451v1 [cs.NE])

Modularity is essential to many well-performing structured systems, as it is
a useful means of managing complexity [8]. An analysis of modularity in neural
networks produced by machine learning algorithms can offer valuable insight
into the workings of such algorithms and how modularity can be leveraged to
improve performance. However, this property is often overlooked in the
neuroevolutionary literature, so the modular nature of many learning algorithms
is unknown. This property was assessed on the popular algorithm "NeuroEvolution
of Augmenting …

arxiv learning networks reinforcement reinforcement learning